• Sun. Sep 24th, 2023

Research on the influence of digital finance on the economic efficiency of energy industry in the background of artificial intelligence

New energy technologies include solar power generation, water energy, wind energy, tidal energy, sea surface temperature difference energy, wave energy, firewood, peat soil, biochemical material energy conversion, geothermal energy, tar sand, etc. At this stage, it is generally recognized that new energy and renewable resources are based on the development trend of new technology application, and gradually change the development and utilization of renewable resources. The traditional fossil energy resources with environmental pollution problems and limited total amount should be replaced by new energy sources that will not be limited by the total amount and the utilization of the recycling system. The key development areas include solar power generation, tidal energy, hydrogen energy and wind energy.

The new energy industry is the exploration, development and utilization of new energy. It uses social methods to achieve effective utilization and popularization, including the whole process of scientific research, industrial utilization, production, manufacturing and operation. It is a high-tech that commercializes solar power generation, wind energy, bioenergy, etc. From the perspective of the characteristics of the industrial chain, the new energy industry is to replace the new industries with strategic status represented by fossil energy, and has extremely important obligations in replacing fossil energy, promoting economic growth, protecting the environment, and building a harmonious society; From the perspective of the whole industry chain, the new energy industry can be divided into energy supply, product research and development, investment and manufacturing, transportation and trading.

The Corona Virus Disease 2019 pandemic has had a major impact on the traditional financial services provided by financial institutions, but it has also accelerated the digital transformation of these services. According to the statistics and analysis of the China Asset Appraisal Association, during the epidemic period, the average service item replacement rate of online banking reached 96%. Despite the epidemic’s considerable effects on small and micro businesses and traditional financial “long-tail clients”, However, under the background of the intelligent era, the development speed of digital banking is enough to solve the problems of these groups. Through “zero contact” to provide them with low-cost, convenient and fast service projects, especially the contact-free loan has become an important means to help the sustainable development of the energy industry10.

The development of digital finance requires a complete institutional system, and the institutional system of digital finance is the financial ecosystem, which is composed of the main body of the ecosystem and the financial ecological environment. The close combination of the two can produce a regular financial ecosystem with internal logic and self-improvement. Judging from the current overall situation of China’s financial institution management system, it has basically formed a large digital financial service ecological chain dominated by banking, Internet banking, non-bank finance, and large and medium-sized financial high-tech companies with electronic payment system, integrity management system, legal norms as infrastructure and institutional guarantee, which is dominated by the “one committee, one bank, two committees and one bureau” supervisory agency11,12. A schematic representation of the structure of the digital financial ecosystem is given in Fig. 1.

Figure 1
figure 1

Digital financial ecosystem.

At this point, a significant trend is the close integration of digital technology with finance. In the era of artificial intelligence, digital technology is playing a unique and important role in modern finance. The following points mostly highlight the benefits of digital finance: Firstly, by increasing financing channels, the threshold for financial services has been lowered; secondly, by greatly reducing service prices, comprehensive financial services have achieved sustainable development; thirdly, the personalized financial services can better meet the various requirements of different users; the fourth is to help reduce information asymmetry and provide new risk management methods13.

According to different levels of financial functions, digital finance can be divided into three categories: basic functions, leading functions and derivative functions. Figure 2 shows the mechanism of digital finance on the efficiency of urban green development. There are three behavioral paths for the above three functions. The first is digital finance → intermediary services → inclusive utility. Digital finance uses digital information technology to manufacture and expand the role of finance. The network effect of digital technology expands the boundaries of traditional financial services and reduces the service cost of traditional finance. The scale and economic characteristics of digital finance reduce the entry threshold and related costs for innovative enterprises. At the same time, by relying on digital technology, the ability to obtain data and analyze information has been greatly improved and the information asymmetry and the cost of credit intermediary companies have been reduced, and the credit environment has been optimized. After building a three-dimensional credit image based on enterprise big data and cloud technology, sporadic enterprises and start-up companies that are difficult to obtain the support of traditional credit services would obtain a high probability of credit. In order to increase the effectiveness of the urban green economy, the development of digital finance would also help traditional finance change and grow. It would also make full use of the complementary roles that traditional finance and digital finance play in advancing economic growth. Therefore, digital finance will promote the development of traditional finance, and will promote the economic development of the energy industry, and achieve the effect of improving the economic efficiency of the energy industry14,15.

Figure 2
figure 2

The impact of digital finance on how well urban green development is carried out.

The second is digital finance → resource allocation service → upgrade utility. Resource allocation service is the core role of finance and an excellent way to correctly guide use value. On the one hand, the birth of digital finance has promoted competition among financial formats and enhanced the charm of folk capital and the financial system, and improved the efficiency and capability of capital allocation. The use of artificial intelligence and electronic information technology can better match the investment needs and financing needs, reduce the financing pressure of the energy industry, and make the capital used more efficiently and quickly for innovation. On the other hand, the circulation of capital factor commodities has been improved. For a long time, in the factor market, the government department has the dominance and dominance of the vast majority of manufacturing factors, and there may be behaviors such as abuse of power. In addition, the popularity of local protectionism and the emergence of administrative systems have resulted in serious market segmentation. The inconsistency and segmentation of the elements of the sales market make some enterprises, especially state-owned enterprises, lose the driving force of “self-innovation”. This harms the development of the urban green economy’s efficiency. To provide enough financial factors for the supply-side structure’s green development, Digital finance enables the energy industry to overcome regional barriers and enhance the environment for the free flow of capital. Therefore, by enhancing and upgrading the efficiency of regional capital element allocation, data finance can achieve the effect of boosting the efficiency of urban green economy16.

The third is digital finance → redistribution of finance → inclusive utility. The rapid development of inclusive finance, on the one hand, helps low-income people get rid of poverty and become rich, which improves the level of per capita consumption and promotes economic transformation and upgrading; on the other hand, with the expansion of the number of netizens and network coverage and the rapid rise of e-commerce and Internet consumer finance, the consumption structure of urban residents has also gradually changed. The demand-side consumption capacity and consumption structure have been upgraded, and the energy industry has increased its demand for high-quality products. This has prompted the energy industry to expand the scope of its technology investment and product development efforts, and to encourage the growth of a local green economy. Therefore, digital financing encourages the energy industry to expand technology investment and product research and development, which has the effect of improving the efficiency of urban green economy17.

The energy industry is an indispensable part of economic development. Digital finance provides loans to small and medium-sized energy enterprises to meet the financing needs of small and medium-sized energy enterprises, thus stimulating regional economic growth. However, these small and medium-sized energy enterprises are struggling with financial problems and high financing costs. Only a small number of enterprises can apply for loans from financial institutions through official channels, and other enterprises are under pressure of capital loans. The growth of financial inclusion through digital means has reduced borrowing costs and simplified processes. By providing special loans to such enterprises to help them improve their financing and risk management capabilities, it will help improve their profitability and ultimately improve China’s economic growth rate18,19.

If the capital supply cannot keep up, there will be a lock-in effect, and it is imperative to get rid of this inefficient equilibrium state. The basic strategy is to provide specific capital elements for the energy industry, so the assistance of participating banks is essential, and micro loans for small and medium-sized energy industries can help them achieve higher output. Continuous investment in capital and technology will reduce marginal costs, which will have an impact on increasing output and income20,21. As shown in Fig. 3, the structure of micro credit’s anti lock support effect.

Figure 3
figure 3

Anti-lock-in support effect structure diagram of microfinance.

This paper discusses the impact of digital finance on the economic efficiency of the energy industry in the context of artificial intelligence. The calculation formula of some indicators related to the measurement of the economic efficiency of the energy industry is as follows:

$$GTFP_au=\sigma _0+\sigma _1GTFP_a,u-1+\sigma _2df_au+\sigma _3df2_au+\sigma _bT_bau+\theta _a+\varepsilon _a+\omega _au.$$


\(T\)-set of control variables; \(GTFP_au\)-Green economic efficiency of energy industry; \(df_au\)-digital finance; \(df2_au\)-square term of digital finance; \(\omega _au\)-disturbance term; \(\theta _a\)-time fixed effect

$$n_au=m_au\prime\sigma +\left(1,m_au^\prime\right)\rho 1\left(g_au>\varphi \right)+\theta _a+\omega _au,$$


\(m_au^\prime\)-a collection of independent variables; \(\mathrmg_\mathrmau\)-threshold variables

$$GTFP_au=\sigma _0+\sigma _1GTFP_a,u-1+\sigma _2df_au+\sigma _3df2_au+\sigma _bT_bau+distrk_au+\theta _a+\varepsilon _a+\omega _au,$$


$$distrk=\sigma _0+\sigma _1distrk_a,u-1+\sigma _2df_au+\sigma _3df2_au+\sigma _bT_bau+\theta _a+\varepsilon _a+\omega _au,$$


\(distrk\)-degree of capital misallocation

$$\mathrmlngdp_\mathrmau=\updelta _0+\updelta _1\mathrmlncapital_\mathrma,\mathrmu+\updelta _2\mathrmlnlabor_\mathrma,\mathrmu+\frac12\times \updelta _3\left(\mathrmlncapital_\mathrma,\mathrmu\right)^2+\frac12\times \updelta _4\left(\mathrmlnlabor_\mathrma,\mathrmu\right)^2+\updelta _5\mathrmlncapital_\mathrma,\mathrmu\times \mathrmlnlabor_\mathrma,\mathrmu+\omega _au,$$


\(\mathrmlngdp_\mathrmau\)-degree of capital distortion

$$MP_au=\left(\delta _1+\delta _3lncapital_a,u+\delta _5lnlabor_a,u\right)\times \fracgdp_aucaptial_au,$$


\(MP_au\)-margin of capital

$$min\gamma =\frac1-\frac1K\sum_k=1^K\fracX_k^dd_k01+\frac1L+1\left(\sum_l=1^L\fracX_l^ee_l0+\sum_j=1^J\fracX_j^zz_j0\right),$$


\(\mathrmd\)\(\mathrmd\) kinds of inputs; L-L kinds of expected outputs; J-J kinds of undesired outputs; \(\upgamma \)-green total factor productivity efficiency value.


$$\sum_v=1^Vm_gd_kg+X_k^d=d_k0,k=\mathrm1,2,\cdots ,K$$


$$\sum_v=1^Vm_ge_lg-X_l^d=e_l0,l=\mathrm1,2,\cdots ,L$$


$$\sum_v=1^Vm_gz_jg+X_j^z=z_j0,j=\mathrm1,2,\cdots ,J.$$


Let the formulas be:

$$X_k^d\ge 0, X_l^d\ge 0, X_j^z\ge 0, m_g\ge 0$$




$$cap_au=\left(1-\propto _a\right)cap_a,u-1+F_a,u-1,$$


\(\mathrmcap_\mathrmau\)-fixed capital stock of the whole society; \(\propto _\mathrma\)-capital depreciation rate

$$cap_a,0=\fracF_a,1o_a+\propto _a,$$


\(\mathrmcap_\mathrma,0\)-cap initial capital stock; \(\mathrmo_\mathrma\)-cap average annual growth rate.


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